Estimation of Solar Diffuse Radiation in Chongqing Based on Random Forest - Peihan Wan; Yongjian He; Chaoyu Zheng; Jiaxiong Wen; Zhuting Gu (Energies)
Solar diffuse radiation (DIFRA) is an important component of solar radiation, but current research into the estimation of DIFRA is relatively limited. This study, based on remote sensing data, topographic data, meteorological reanalysis materials, and measured data from radiation observation stations in Chongqing, combined key factors such as the solar elevation angle, water vapor, aerosols, and cloud cover. A high-precision DIFRA estimation model was developed using the random forest algorithm, and a distributed simulation of DIFRA in Chongqing was achieved. The model was validated using 8179 measured data points, demonstrating good predictive capability with a correlation coefficient (R2) of 0.72, a mean absolute error (MAE) of 35.99 W/m2, and a root mean square error (RMSE) of 50.46 W/m2. Further validation was conducted based on 14 radiation observation stations, with the model demonstrating high stability and applicability across different stations and weather conditions. In particular, the fit was optimal for the model under overcast conditions, with R2 = 0.70, MAE = 32.20 W/m2, and RMSE = 47.51 W/m2. The results indicate that the model can be effectively adapted to all weather calculations, providing a scientific basis for assessing and exploiting solar energy resources in complex terrains.